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Deep learning for PET image reconstruction

some current approaches

##article.authors##

  • Fumio Hashimoto Central Research Laboratory, Hamamatsu Photonics K.K.
  • Reader, Andrew School of Biomedical Engineering and Imaging Sciences, King’s College London

DOI:

https://doi.org/10.51094/jxiv.615

Keywords:

PET image reconstruction, deep learning

Abstract

Deep learning has long been applied to PET image reconstruction. In this brief review, we first cover a brief history of PET image reconstruction as well as a straightforward explanation of deep learning-based PET image reconstruction, from the basic ideas of deep learning reconstruction to some of the most recent research developments.

Conflicts of Interest Disclosure

There is no conflict of interest.

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References

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［11］ Hashimoto F, Ote K, Onishi Y: PET image reconstruction incorporating deep image prior and a forward projection model. IEEE Trans Radiat Plasma Med Sci 6: 841-846, 2022

［12］ Hashimoto F, et al.: Fully 3D implementation of the end-to-end deep image prior-based PET image reconstruction using block iterative algorithm. Phys Med Biol 68: 155009, 2023

［13］ Ote K, et al: List-Mode PET Image Reconstruction Using Deep Image Prior. IEEE Trans Med Imaging 72: 1822-1834 2023

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［16］ Hashimoto F, et al: Deep learning-based PET image denoising and reconstruction: a review. Radiol Phys Technol, 2024. doi: 10.1007/s12194-024-00780-3

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Submitted: 2024-02-02 01:53:41 UTC

Published: 2024-02-07 01:05:17 UTC
Section
Information Sciences

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Copyright (c) 2024 Fumio Hashimoto
Reader, Andrew

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.